Hongze Wang (Southeast University), Zhen Ling (Southeast University), Xiangyu Xu (Southeast University), Yumingzhi Pan (Southeast University), Guangchi Liu (Southeast University), Junzhou Luo (Southeast University and Fuyao University of Science and Technology), Xinwen Fu (University of Massachusetts Lowell)

I2P (Invisible Internet Project) is a popular anonymous communication network. While existing de-anonymization methods for I2P focus on identifying potential traffic patterns of target hidden services among extensive network traffic, they often fail to scale effectively across the large and diverse I2P network, which consists of numerous routers. In this paper, we introduce I2PERCEPTION a low-cost approach revealing the IP addresses of I2P hidden services. In I2PERCEPTION, attackers deploy floodfill routers to passively monitor I2P routers and collect their RouterInfo. We analyze the router information publication mechanism to accurately identify routers' join (i.e. on) and leave (i.e. off) behaviors, enabling fine-grained live behavior inference across the I2P network. Active probing is used to obtain the live behavior (i.e., on-off patterns) of a target hidden service hosted on one of the I2P routers. By correlating the live behaviors of the target hidden service and I2P routers over time, we narrow down the set of routers matching the hidden service's behavior, revealing the hidden service's true network identity for de-anonymization. Through the deployment of only 15 floodfill routers over the course of eight months, we validate the precision and effectiveness of our approach with extensive real-world experiments. Our results show that I2PERCEPTION successfully de-anonymizes all controlled hidden services.

View More Papers

Towards automated threat modeling for space systems via SPARTA...

Joonhyuk Park (School of Cybersecurity, Korea University), Jiwon Kwak (School of Cybersecurity, Korea University), Geunwoo Baek (School of Cybersecurity, Korea University), Dohee Kang (School of Cybersecurity, Korea University), Seungjoo Kim (School of Cybersecurity, Korea University)

Read More

Context Relay for Long-Running Penetration-Testing Agents

Marius Vangeli (KTH Royal Institute of Technology, Sweden), Joel Brynielsson (KTH Royal Institute of Technology, Sweden and FOI Swedish Defence Research Agency, Sweden), Mika Cohen (KTH Royal Institute of Technology, Sweden and FOI Swedish Defence Research Agency, Sweden), Farzad Kamrani (FOI Swedish Defence Research Agency, Sweden)

Read More

The Case for LLM-Enhanced Backward Tracking

Jiahui Wang (Zhejiang University, Hangzhou, China), Xiangmin Shen (Hofstra University, Hempstead, NY, USA), Zhengkai Wang (Zhejiang University, Hangzhou, China), Zhenyuan Li (Zhejiang University, Hangzhou, China)

Read More